DEVELOPMENT OF THE REAL-TIME RIVER STAGE PREDICTION METHOD USING DEEP LEARNING-Reference-Cited by-同舟云学术

DEVELOPMENT OF THE REAL-TIME RIVER STAGE PREDICTION METHOD USING DEEP LEARNING

Published:2017 Issue:1 Volume:5 Page:422-429
ISSN:2187-5103
Container-title:Journal of JSCE
language:en
Short-container-title:Journal of JSCE

Author:

HITOKOTO Masayuki¹,SAKURABA Masaaki¹,SEI Yuichi²

Affiliation:

1. Research and Development Center, Nippon Koei Co., Ltd.

2. Graduate School of Informatics and Engineering, University of Electro-Communications

Publisher

Japan Society of Civil Engineers

Subject

Civil and Structural Engineering,Environmental Engineering

Link

https://www.jstage.jst.go.jp/article/journalofjsce/5/1/5_422/_pdf

Reference14 articles.

1. 1) Tachikawa, Y., Nagatani, G. and Takara, K. : Development of stage-discharge relationship equation incorporating saturated-unsaturated flow mechanism, Annual Journal of Hydraulics Engineering, Vol. 48, pp. 7-12, 2004 (in Japanese).

2. 2) Suzuki, T., Terakawa, A. and Matsuura T. : Jitsu jikan yosoku no tame no bunpugata model no kaihatsu (Development of the distributed model for real-time flood prediction), Civil Engineering Journal, Vol. 38-10, pp. 26-31, 1996 (in Japanese).

3. 3) ASCE Task Committee on Application of Artificial Neural Networks in Hydrology : Artificial neural networks in hydrology. II : Hydrologic Applications, Journal of Hydrologic Engineering, Vol. 5, No. 2, 2000.

4. 4) Dawson, C. W. and Wilby, R. L. : Hydrological modeling using artificial neural networks, Progress in Physical Geography, Vol. 25, No. 1, 2001.

5. 5) Maier, H. R. and Dandy, G. C. : Neural networks for the prediction and forecasting of water resources variables: A review of modelling issues and applications, Environmental Modelling & Software, Vol. 15, 2000.

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